Comprehensive side-by-side LLM comparison
GPT-4.1 nano offers 810.0K more tokens in context window than Qwen3-Coder-480B. GPT-4.1 nano is $1.00 cheaper per million tokens. GPT-4.1 nano supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
OpenAI
GPT-4.1 nano is OpenAI's smallest member of the GPT-4.1 family, released in April 2025 alongside GPT-4.1 and GPT-4.1 mini as the latency-optimized, cost-minimized option for high-throughput applications. Positioned below GPT-4.1 mini in both size and cost, it was designed for use cases where speed and affordability dominate over raw capability — including tool calling, intent classification, short-form instruction following, and retrieval-augmented lookup tasks. Unlike its larger siblings, it supports fine-tuning, making it a practical candidate for task-specific customization at scale without incurring the cost of fine-tuning larger models.
Alibaba / Qwen
Qwen3-Coder-480B-A35B-Instruct, released by Alibaba's Qwen team on July 22, 2025, is a Mixture-of-Experts large language model with 480 billion total parameters and 35 billion active parameters per inference, specifically designed for agentic coding tasks. It features a 256K token native context window (extendable to 1M tokens with extrapolation) and demonstrated competitive performance on agentic coding, browser automation, and tool-use benchmarks. Qwen3-Coder-480B targets automated software engineering, multi-step code agents, and open-source coding deployments under the Apache 2.0 license.
3 months newer

GPT-4.1 nano
OpenAI
2025-04-14
Qwen3-Coder-480B
Alibaba / Qwen
2025-07-22
Cost per million tokens (USD)
GPT-4.1 nano
Qwen3-Coder-480B
Context window and performance specifications
GPT-4.1 nano
2024-06
Available providers and their performance metrics
GPT-4.1 nano
OpenAI
Qwen3-Coder-480B
GPT-4.1 nano
Qwen3-Coder-480B
GPT-4.1 nano
Qwen3-Coder-480B
OpenRouter